GPT-4o System Card
This model addresses the need for faster, cheaper, and more capable multimodal AI systems for general users and developers, though it appears incremental as an extension of existing GPT technology.
The paper introduces GPT-4o, an autoregressive omni model that processes any combination of text, audio, image, and video inputs to generate text, audio, and image outputs, achieving human-like response times (as low as 232 ms) and matching GPT-4 Turbo performance in English and code while being 50% cheaper and faster. It shows significant improvements in non-English languages, vision, and audio understanding.
GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs and outputs are processed by the same neural network. GPT-4o can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50\% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models. In line with our commitment to building AI safely and consistent with our voluntary commitments to the White House, we are sharing the GPT-4o System Card, which includes our Preparedness Framework evaluations. In this System Card, we provide a detailed look at GPT-4o's capabilities, limitations, and safety evaluations across multiple categories, focusing on speech-to-speech while also evaluating text and image capabilities, and measures we've implemented to ensure the model is safe and aligned. We also include third-party assessments on dangerous capabilities, as well as discussion of potential societal impacts of GPT-4o's text and vision capabilities.